This report is constructed purely to produce figures for the VPD-COVID phase I modelling work.

d_pop <- readRDS("d_pop.rds")
figure_maker_burden_per_mod_dis(d_pop, burden_t = "deaths", scenario_pal, 
                                            year_end = 2030, dis_name = "Yellow fever")
Deaths per year up to 2030 for Yellow Fever.

Deaths per year up to 2030 for Yellow Fever.

figure_maker_burden_per_mod_dis(d_pop, burden_t = "deaths", scenario_pal, 
                                            year_end = 2030, dis_name = "Measles")
Deaths per year up to 2030 for Measles.

Deaths per year up to 2030 for Measles.

figure_maker_burden_per_mod_dis(d_pop, burden_t = "deaths", scenario_pal, 
                                            year_end = 2030, dis_name = "Meningitis A")
Deaths per year up to 2030 for Yellow Fever.

Deaths per year up to 2030 for Yellow Fever.

figure_maker_burden_per_mod_dis_pop(d_pop, burden_t = "deaths", scenario_pal, 
                                            year_end = 2030, dis_name = "Yellow fever")
Deaths per 100,000 per year up to 2030 for Yellow Fever.

Deaths per 100,000 per year up to 2030 for Yellow Fever.

figure_maker_burden_per_mod_dis_pop(d_pop, burden_t = "deaths", scenario_pal, 
                                            year_end = 2030, dis_name = "Measles")
Deaths per 100,000 per year up to 2030 for Measles.

Deaths per 100,000 per year up to 2030 for Measles.

figure_maker_burden_per_mod_dis_pop(d_pop, burden_t = "deaths", scenario_pal, 
                                            year_end = 2030, dis_name = "Meningitis A")
Deaths per 100,000 per year up to 2030 for Yellow Fever.

Deaths per 100,000 per year up to 2030 for Yellow Fever.

figure_maker_burden(d_pop, burden_t = "deaths", scenario_pal)
Deaths per year up to 2030 for the model averaged predictions for (A) Measles, (B) Meningitis A and (C) Yellow Fever. Dotted lines indicate each modelling group whereas the solid line represents the mean.

Deaths per year up to 2030 for the model averaged predictions for (A) Measles, (B) Meningitis A and (C) Yellow Fever. Dotted lines indicate each modelling group whereas the solid line represents the mean.

figure_maker_burden(d_pop, burden_t = "dalys", scenario_pal)
DALYs per year up to 2030 for the model averaged predictions for (A) Measles, (B) Meningitis A and (C) Yellow Fever. Dotted lines indicate each modelling group whereas the solid line represents the mean.

DALYs per year up to 2030 for the model averaged predictions for (A) Measles, (B) Meningitis A and (C) Yellow Fever. Dotted lines indicate each modelling group whereas the solid line represents the mean.

figure_maker_burden_ribbon(d_pop, burden_t = "deaths", scenario_pal)
Deaths per year up to 2030 for the model averaged predictions for (A) Measles, (B) Meningitis A and (C) Yellow Fever. Grey ribbon represents the envelope of all model predictions - this should not be interpreted as uncertainty.

Deaths per year up to 2030 for the model averaged predictions for (A) Measles, (B) Meningitis A and (C) Yellow Fever. Grey ribbon represents the envelope of all model predictions - this should not be interpreted as uncertainty.

figure_maker_burden_ribbon(d_pop, burden_t = "dalys", scenario_pal)
DALYs per year up to 2030 for the model averaged predictions for (A) Measles, (B) Meningitis A and (C) Yellow Fever.  Grey ribbon represents the envelope of all model predictions - this should not be interpreted as uncertainty.

DALYs per year up to 2030 for the model averaged predictions for (A) Measles, (B) Meningitis A and (C) Yellow Fever. Grey ribbon represents the envelope of all model predictions - this should not be interpreted as uncertainty.

d_burden <-
    d_pop %>%
    filter(burden_outcome == "deaths") %>%
    filter(year %in% c(2020, 2030)) %>%
    group_by(country, year, modelling_group, simple_scenario, disease) %>%
    summarise(value = sum(focal_burden, na.rm = TRUE)) %>%
    bind_rows(d %>% 
                filter(burden_outcome == "deaths", 
                       simple_scenario == "Postpone 2020 SIAs -> 2021", 
                       year %in% c(2020, 2030)) %>%
                group_by(country, year, disease, modelling_group) %>%
                summarise(value = sum(baseline_burden, na.rm = TRUE)) %>%
                mutate(simple_scenario = "BAU"))

d_burden %>% 
  filter(country == "NGA") %>%
  arrange(year, disease) %>%
  mutate(value = round(value)) %>%
  pivot_wider(names_from = simple_scenario,
              values_from = value) %>% 
  flextable::flextable(cwidth = 1.5)
figure_maker_burden_pop(d_pop, burden_t = "deaths", scenario_pal)
Deaths per 100,000 per year up to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever. Dotted lines indicate each modelling group whereas the solid line represents the mean.

Deaths per 100,000 per year up to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever. Dotted lines indicate each modelling group whereas the solid line represents the mean.

figure_maker_burden_pop(d_pop, burden_t = "dalys", scenario_pal)
DALYs per 100,000 per year up to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever. Dotted lines indicate each modelling group whereas the solid line represents the mean.

DALYs per 100,000 per year up to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever. Dotted lines indicate each modelling group whereas the solid line represents the mean.

figure_maker_burden_per_pop_ribbon(d_pop, burden_t = "deaths", scenario_pal)
Deaths per 100,000 per year up to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever. Grey ribbon represents the envelope of all model predictions - this should not be interpreted as uncertainty.

Deaths per 100,000 per year up to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever. Grey ribbon represents the envelope of all model predictions - this should not be interpreted as uncertainty.

figure_maker_burden_per_pop_ribbon(d_pop, burden_t = "dalys", scenario_pal)
DALYs per 100,000 per year up to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever. Grey ribbon represents the envelope of all model predictions - this should not be interpreted as uncertainty.

DALYs per 100,000 per year up to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever. Grey ribbon represents the envelope of all model predictions - this should not be interpreted as uncertainty.

Effect by country

figure_maker_excess_country(d_pop, "deaths", scenario_pal)
Excess deaths per year from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever by country. The error bars range from max to min group preditions.

Excess deaths per year from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever by country. The error bars range from max to min group preditions.

figure_maker_excess_country(d_pop, "dalys",  scenario_pal)
Excess DALYs per year from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever by country. The error bars range from max to min group preditions.

Excess DALYs per year from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever by country. The error bars range from max to min group preditions.

figure_maker_excess_country_pop(d_pop, "deaths", scenario_pal)
Excess deaths per 100,000 population per year from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever by country.The error bars range from max to min group preditions.

Excess deaths per 100,000 population per year from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever by country.The error bars range from max to min group preditions.

figure_maker_excess_country_pop(d_pop, "dalys",  scenario_pal)
Excess DALYs per 100,000 population per year from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever by country.The error bars range from max to min group preditions.

Excess DALYs per 100,000 population per year from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever by country.The error bars range from max to min group preditions.

Normalised impact

figure_maker_norm(d_pop, "deaths", scenario_pal)
Normalised excess deaths from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever.

Normalised excess deaths from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever.

figure_maker_norm_per_country(d_pop, "deaths", scenario_pal)
Normalised excess deaths from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever per country

Normalised excess deaths from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever per country

figure_maker_norm(d_pop, "dalys", scenario_pal)
Normalised excess DALYs from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever.

Normalised excess DALYs from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever.

figure_maker_norm_per_country(d_pop, "dalys", scenario_pal)
Normalised excess DALYs from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever per country

Normalised excess DALYs from 2020 to 2030 for the model averaged predictions for Measles, Meningitis A and Yellow Fever per country

figure_maker_norm(d_pop, "deaths", scenario_pal, year_end = 2100)
Normalised excess deaths from 2020 to 2100 for the model averaged predictions for Measles, Meningitis A and Yellow Fever.

Normalised excess deaths from 2020 to 2100 for the model averaged predictions for Measles, Meningitis A and Yellow Fever.

figure_maker_norm_per_country(d_pop, "deaths", scenario_pal, year_end = 2100)
Normalised excess deaths from 2020 to 2100 for the model averaged predictions for Measles, Meningitis A and Yellow Fever per country

Normalised excess deaths from 2020 to 2100 for the model averaged predictions for Measles, Meningitis A and Yellow Fever per country

figure_maker_norm(d_pop, "dalys", scenario_pal, year_end = 2100)
Normalised excess DALYs from 2020 to 2100 for the model averaged predictions for Measles, Meningitis A and Yellow Fever.

Normalised excess DALYs from 2020 to 2100 for the model averaged predictions for Measles, Meningitis A and Yellow Fever.

figure_maker_norm_per_country(d_pop, "dalys", scenario_pal, year_end = 2100)
Normalised excess DALYs from 2020 to 2100 for the model averaged predictions for Measles, Meningitis A and Yellow Fever per country

Normalised excess DALYs from 2020 to 2100 for the model averaged predictions for Measles, Meningitis A and Yellow Fever per country

Adding under 5 burden

d_pop %>%
  filter(year<=2030)  %>%
  filter(grepl("deaths", burden_outcome)) %>%
  mutate(under5 = ifelse(grepl("under5", burden_outcome),
                         "<5",
                         "All ages")) %>%
  group_by(modelling_group_tidy, simple_scenario, disease, under5) %>%
  summarise(Excess = -sum(impact, na.rm = TRUE)) %>%
  mutate(Excess = round(Excess)) %>%
  mutate(disease = factor(disease, levels = rev(c("Measles", "Meningitis A", "Yellow fever")))) %>%
  mutate(mod_grp_dis = paste0(disease, ", ",modelling_group_tidy)) %>%
  
  ggplot()+
  geom_col(position = "dodge", color = "black")+
  aes(x = mod_grp_dis, y = Excess, fill = under5)+
  coord_flip()+
  facet_wrap(simple_scenario~., nrow = 2, scales = "free_y")+
  theme_minimal()+
  scale_fill_manual(values = c("black", "white"))+
  labs(y = "Excess deaths", x = "", fill = "Age" )